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Karishma Agrawal [email protected] www.andrew.cmu.edu/user/kdagrawa 5530 Fifth Avenue, Apt# GFB Pittsburgh, PA 15232 412-961-4436 EDUCATION Carnegie Mellon University Pittsburgh, PA Master of Information Systems Management December 2015 Concentration of Business Intelligence and Data Analytics GPA 3.55/4.33 Relevant Courses: Machine Learning, Machine Learning for Large Data, Data Mining, Machine Learning for Signal Processing Sardar Vallabhbhai National Institute of Technology (NIT-Surat) Bachelor of Technology, Computer Engineering Bronze Medal for Academic Performance Surat, India May 2014 GPA 9.22/10 SKILLS Languages APIs/Tools Databases : Python, Java, C, R, SQL, PL SQL, Assembly Language, Shell Scripting : Apache Hadoop, MATLAB, Twitter API : Apache Cassandra, My SQL, SQL Server EXPERIENCE Sony Corporation Tokyo, Japan Research and Development Engineering Intern June – August 2015 § Carried out research and development activities in advanced intelligent technologies department in the domain of deep learning. § Developed and implemented Convolution Neural Network and Recurrent Neural Network based solutions for sleep detection and human activity detection. Impetus Infotech Pvt. Ltd. Indore, India Data Intern May − July 2013 § Developed a programmer friendly, scalable Machine Learning Library to support and simplify the development of future projects. § Worked with various technologies such as Apache Hadoop, Apache Cassandra, Apache Mahout, MapReduce and Weka. § Programmed ML algorithms such as kNN on MapReduce paradigm. Department of Computer Engineering, S.V.N.I.T. Surat, India Summer Intern May − June 2012 § Performed a literature survey and implemented few applications of Cellular Automata, using Matlab, in fields of image processing, data mining and cryptography. § Studied Temporal Data Mining and implemented data association using sliding window and Apriori algorithm. ACADEMIC PROJECTS Multilingual Path Ranking Algorithm, CMU March – May 2015 § Studied and extended the Path Ranking Algorithm implemented by CMU-LTI PhD candidate, for multilingual data. § Included vector space embedding and external language translation matrix to improve the inference confidence. § Conducted experiments using mixed language corpus, followed by training in one language and testing in another language. Pump It Up: Data Mining for Tanzania Water Crisis, CMU March – May 2015 § Conducted classification of water pumps in different categories, prioritizing identification of pumps that need repair. § Dealt with skewed class distribution and features with extremely high arity. § Used Random Forest for final model with appropriate operating point to minimize false positive rates. Human Activity Recognition, CMU January – March 2015 § Analyzing the data from multiple accelerometers worn at different parts of the body, to predict the user activity. § The temporal nature of data was exploited and analyzed, apart from data preprocessing and feature engineering. Object Recognition using Discriminative Features and Linear Classifier, CMU December 2014 § Carried out feature engineering using various techniques such as PCA, ZCA, mirroring, and Kmeans clustering on the CIFAR-10. § Tested classification accuracy of transformed features using linear classifiers such as Multinomial Logistic Regression and Support Vector Machines. Regression Analysis to Determine Effort Required for Software Maintenance, CMU October 2014 § Used hypothesis testing and regression analysis to make decisions on software development practices and analyzed how various independent factors affect software maintenance time. EXTRACURRICULAR EXPERIENCE Admissions Ambassador, CMU March 2015 - present Career Services Host, CMU January 2015 - present ACM International Collegiate Programming Contest, Asia Regionals, Kharagpur, India November 2012 IBM Web Technical Contest, India November 2011 § Given Special Recognition for best paper in “Role of Women in Technology”, with an idea to improve the emergency calling system with aim of improving security for women; presented the idea on wider forum through Webinar using WebEx.
